SARS-CoV-2 and other airborne respiratory viruses in outdoor aerosols in three Swiss cities before and during the first wave of the COVID-19 pandemic

Abstract

Caused by the SARS-CoV-2 virus, Coronavirus disease 2019 (COVID-19) has been affecting the world since the end of 2019. While virus-laden particles have been commonly detected and studied in the aerosol samples from indoor healthcare settings, studies are scarce on air surveillance of the virus in outdoor non-healthcare environments, including the correlations between SARS-CoV-2 and other respiratory viruses, between viruses and environmental factors, and between viruses and human behavior changes due to the public health measures against COVID-19. Therefore, in this study, we collected airborne particulate matter (PM) samples from November 2019 to April 2020 in Bern, Lugano, and Zurich. Among 14 detected viruses, influenza A, HCoV-NL63, HCoV-HKU1, and HCoV-229E were abundant in air. SARS-CoV-2 and enterovirus were moderately common, while the remaining viruses occurred only in low concentrations. SARS-CoV-2 was detected in PM₁₀ (PM below 10 µm) samples of Bern and Zurich, and PM_2.5 (PM below 2.5 µm) samples of Bern which exhibited a concentration positively correlated with the local COVID-19 case number. The concentration was also correlated with the concentration of enterovirus which raised the concern of coinfection. The estimated COVID-19 infection risks of an hour exposure at these two sites were generally low but still cannot be neglected. Our study demonstrated the potential functionality of outdoor air surveillance of airborne respiratory viruses, especially at transportation hubs and traffic arteries.

Keywords: Air pollution; Airborne respiratory virus; Bioaerosol; COVID-19; SARS-CoV-2; Surveillance.

Graphical abstract

Fig. 1

The sampling locations (a) and time periods (b).

Fig. 2

The absolute abundance of viruses in all air samples (log₁₀(copies/m³ + 1), A and B after the abbreviations of the months stand for the first half and second half of that month).

Fig. 3

The abundance of SARS-CoV-2 and new case number in the local cantons (A and B after the abbreviations of the months stand for the first half and second half of that month).

Fig. 4

The co-occurrence network of the airborne viruses in PM2.5 (left) and PM10 (right) (orange lines stand for positive correlation, blue lines for negative correlation, the widths of the lines indicate the relative size of the coefficient, and the sizes of the circles show the relative viral abundances). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Fig. 5

The RDA analysis of all target airborne viruses in PM2.5 (left）and PM10 (right) and environmental factors in three cities (A and B after the abbreviations of the months stand for the first half and second half of that month).

Fig. 6

The Co-occurrence network of the airborne viruses and environmental factors in PM2.5 (left) and PM10 (right) (orange lines stand for positive correlation, blue lines stand for negative correlation, the widths of the lines stand for the relative size of the coefficient, and the sizes of the circles stand for the relative concentrations). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Fig. 7

Infection risk of different respiratory viruses through aerosol transmission from 1 h of exposure (a. Influenza A, b. Influenza B, c. HCoV-NL63, d. HCoV-OC43, e. HCoV-HKU1, f. HCoV-229E, g. SARS-CoV-2 with background interference, h. SARS-CoV-2 without background interference. A and B after the abbreviations of the months stand for the first half and second half of that month.).